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Resolve Mouse Marker

resolve_marker
Read-onlyIdempotent

Resolve mouse marker references to canonical MGI records using symbols, MGI IDs, or human orthologs, returning the matching result.

Instructions

Resolve any mouse marker reference to its canonical MGI record. Accepts a mouse symbol (current or synonym, case-insensitive), an MGI id (MGI:98968 or 98968), OR a human gene symbol / HGNC id (resolved to the mouse ortholog). Returns {mgi_id, symbol, name, marker_type, match_type (mgi_id|current|synonym|ortholog)}. An ambiguous symbol returns an ambiguous_query error with the candidate list (not silently picked). A human symbol identical to the mouse symbol resolves as match_type=current (case collision) rather than ortholog; the marker is the same. Signature: resolve_marker(query, response_mode=).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesA mouse marker symbol (current or synonym, case-insensitive), an MGI id (MGI:98968 or 98968), or a human gene symbol / HGNC id for the ortholog.
response_modeNoVerbosity: minimal | compact | standard | full (default compact).compact

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successNo
_metaNo
error_codeNo
messageNo
retryableNo
recovery_actionNo
fieldNo
allowed_valuesNo
hintNo
candidatesNo
queryNo
mgi_idNo
symbolNo
nameNo
marker_typeNo
feature_typeNo
locationNo
match_typeNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate read-only, idempotent, and open-world hints. The description adds behavioral details: the return format (mgi_id, symbol, etc.), the error behavior for ambiguous queries, and the collision handling for human symbols identical to mouse symbols. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-structured, front-loading the main purpose. It includes a signature line with response_mode default, but every sentence adds value. Minor redundancy with the schema for response_mode.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multiple input types, ambiguous resolution, ortholog mapping), the description is thorough. It covers all relevant edge cases and return fields. The output schema exists, so return format is partially covered, but the description complements it well.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with examples and descriptions. The description adds meaning beyond the schema by explaining the match_type field and the edge case of human symbol collision, which is not in the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states explicitly that the tool resolves mouse marker references to canonical MGI records, listing accepted input types. It distinguishes itself from siblings like search_markers or get_marker by focusing on resolution and canonical retrieval.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool, including edge cases such as ambiguous symbols returning an error and human gene symbol collisions. It does not explicitly exclude alternative tools, but the purpose is specific enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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